151 citations · 208 across the 22 of their papers we have counts for
24 papers
Signatures of Steerability in Activation Space of Language Models
Prajjwal Bhattarai, Tuka Alhanai
Steering language models using a set of contrastive representations has been a canonical and computationally efficient method for controlling model behavior. Despite this success i…
Compositional Context Fine-Tuning Vision-Language Model for Complex Assembly Action Understanding from Videos
Hao Zheng, Jinyi Huang, Tiantian Zheng +2
Assembly action understanding is a key enabler for effective human-robot collaborative assembly, yet it remains challenging due to subtle motions and fine-grained hand-object inter…
Polyphony: Diffusion-based Dual-Hand Action Segmentation with Alternating Vision Transformer and Semantic Conditioning
Hao Zheng, Hu Wang, Tiantian Zheng +2
Dual-hand action segmentation, densely predicting actions for both hands from untrimmed videos, is essential for understanding complex bimanual activities. However, it poses severa…
Knowledge distillation through geometry-aware representational alignment
Prajjwal Bhattarai, Mohammad Amjad, Dmytro Zhylko +1
Knowledge distillation is a common paradigm for transferring capabilities from larger models to smaller ones. While traditional distillation methods leverage a probabilistic diverg…
MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks
Lotfi Abdelkrim Mecharbat, Alberto Marchisio, Muhammad Shafique +2
There has been a surge in optimizing edge Deep Neural Networks (DNNs) for accuracy and efficiency using traditional optimization techniques such as pruning, and more recently, empl…
GLoG-CSUnet: Enhancing Vision Transformers with Adaptable Radiomic Features for Medical Image Segmentation
Niloufar Eghbali, Hassan Bagher-Ebadian, Tuka Alhanai +1
Vision Transformers (ViTs) have shown promise in medical image semantic segmentation (MISS) by capturing long-range correlations. However, ViTs often struggle to model local spatia…
Distribution-Free Uncertainty Quantification in Mechanical Ventilation Treatment: A Conformal Deep Q-Learning Framework
Niloufar Eghbali, Tuka Alhanai, Mohammad M. Ghassemi
Mechanical Ventilation (MV) is a critical life-support intervention in intensive care units (ICUs). However, optimal ventilator settings are challenging to determine because of the…
Hybrid Student-Teacher Large Language Model Refinement for Cancer Toxicity Symptom Extraction
Reza Khanmohammadi, Ahmed I. Ghanem, Kyle Verdecchia +9
Large Language Models (LLMs) offer significant potential for clinical symptom extraction, but their deployment in healthcare settings is constrained by privacy concerns, computatio…
The Role of Functional Muscle Networks in Improving Hand Gesture Perception for Human-Machine Interfaces
Costanza Armanini, Tuka Alhanai, Farah E. Shamout +1
Developing accurate hand gesture perception models is critical for various robotic applications, enabling effective communication between humans and machines and directly impacting…
Machine-arranged Interactions Improve Institutional Belonging and Cohesion
Mohammad M. Ghassemi, Tuka Alhanai
We investigated how participation in machine-arranged meetings were associated with feelings of institutional belonging and perceptions of demographic groups. We collected data fro…
An LSTM Feature Imitation Network for Hand Movement Recognition from sEMG Signals
Chuheng Wu, S. Farokh Atashzar, Mohammad M. Ghassemi +1
Surface Electromyography (sEMG) is a non-invasive signal that is used in the recognition of hand movement patterns, the diagnosis of diseases, and the robust control of prostheses.…
The Influence of Biomedical Research on Future Business Funding: Analyzing Scientific Impact and Content in Industrial Investments
Reza Khanmohammadi, Simerjot Kaur, Charese H. Smiley +4
This paper investigates the relationship between scientific innovation in biomedical sciences and its impact on industrial activities, focusing on how the historical impact and con…
The Broad Impact of Feature Imitation: Neural Enhancements Across Financial, Speech, and Physiological Domains
Reza Khanmohammadi, Tuka Alhanai, Mohammad M. Ghassemi
Initialization of neural network weights plays a pivotal role in determining their performance. Feature Imitating Networks (FINs) offer a novel strategy by initializing weights to…
Feature Imitating Networks Enhance The Performance, Reliability And Speed Of Deep Learning On Biomedical Image Processing Tasks
Shangyang Min, Hassan B. Ebadian, Tuka Alhanai +1
Feature-Imitating-Networks (FINs) are neural networks that are first trained to approximate closed-form statistical features (e.g. Entropy), and then embedded into other networks t…
Perception, performance, and detectability of conversational artificial intelligence across 32 university courses
Hazem Ibrahim, Fengyuan Liu, Rohail Asim +36
The emergence of large language models has led to the development of powerful tools such as ChatGPT that can produce text indistinguishable from human-generated work. With the incr…
MambaNet: A Hybrid Neural Network for Predicting the NBA Playoffs
Reza Khanmohammadi, Sari Saba-Sadiya, Sina Esfandiarpour +2
In this paper, we present Mambanet: a hybrid neural network for predicting the outcomes of Basketball games. Contrary to other studies, which focus primarily on season games, this…
Nightly Automobile Claims Prediction from Telematics-Derived Features: A Multilevel Approach
Allen R. Williams, Yoolim Jin, Anthony Duer +2
In recent years it has become possible to collect GPS data from drivers and to incorporate this data into automobile insurance pricing for the driver. This data is continuously col…
Feature Imitating Networks
Sari Saba-Sadiya, Tuka Alhanai, Mohammad M Ghassemi
In this paper, we introduce a novel approach to neural learning: the Feature-Imitating-Network (FIN). A FIN is a neural network with weights that are initialized to reliably approx…
Fetal Gender Identification using Machine and Deep Learning Algorithms on Phonocardiogram Signals
Reza Khanmohammadi, Mitra Sadat Mirshafiee, Mohammad Mahdi Ghassemi +1
Phonocardiogram (PCG) signal analysis is a critical, widely-studied technology to noninvasively analyze the heart's mechanical activity. Through evaluating heart sounds, this techn…
SupCL-Seq: Supervised Contrastive Learning for Downstream Optimized Sequence Representations
Hooman Sedghamiz, Shivam Raval, Enrico Santus +2
While contrastive learning is proven to be an effective training strategy in computer vision, Natural Language Processing (NLP) is only recently adopting it as a self-supervised al…
Exploring a Unified Sequence-To-Sequence Transformer for Medical Product Safety Monitoring in Social Media
Shivam Raval, Hooman Sedghamiz, Enrico Santus +3
Adverse Events (AE) are harmful events resulting from the use of medical products. Although social media may be crucial for early AE detection, the sheer scale of this data makes i…
Artifact Detection and Correction in EEG data: A Review
S Sadiya, T Alhanai, MM Ghassemi
Electroencephalography (EEG) has countless applications across many of fields. However, EEG applications are limited by low signal-to-noise ratios. Multiple types of artifacts cont…
EEG Channel Interpolation Using Deep Encoder-decoder Netwoks
Sari Saba-Sadiya, Tuka Alhanai, Taosheng Liu +1
Electrode "pop" artifacts originate from the spontaneous loss of connectivity between a surface and an electrode. Electroencephalography (EEG) uses a dense array of electrodes, hen…
Spoken Language Biomarkers for Detecting Cognitive Impairment
Tuka Alhanai, Rhoda Au, James Glass
In this study we developed an automated system that evaluates speech and language features from audio recordings of neuropsychological examinations of 92 subjects in the Framingham…